Search

Purpose: Dual-energy (DE) imaging is a method that suppresses bony anatomy on planar kV images while enhancing soft tissue contrast. This technique has been used specifically in the chest to improve the visualization of small lung tumors. However, DE imaging may also provide quantitative information that has not been previously investigated. In this study, the aim was to establish a theoretical relationship between DE image contrast and tumor thickness and to observe this trend in phantom experiments. Methods: A phantom consisting cork (used to simulate lung), tissue-equivalent material, and pork ribs was constructed to test for a relationship between DE image contrast and simulated tumor thickness. Fifteen phantom setups were used with various thicknesses of cork and tissue-equivalent material. For each setup, high (120 kVp) and low (60 kVp) energy planar images were acquired and DE images were produced. The image contrast between the simulated tumor and surrounding tissue was then plotted against the known thicknesses and a linear regression was performed. Results: A linear regression of the contrast data vs simulated tumor thickness resulted in a slope of −0.0454 with an R 2 = 0.9904. The expected uncertainty in the thickness measurements using the regression parameters and DE contrast standard deviation was 0.13 cm. Conclusions: Phantom data exhibited a linear relationship between DE image contrast and simulated tumor thickness. Future studies will investigate patient-specific parameters so that this method can be used clinically to evaluate tumor thickness from planar kV images. Such an approach may have benefits for both adaptive and heavy ion therapies.

Purpose: To evaluate the efficacy of dual-energy (DE) vs single-energy (SE) fluoroscopic imaging of lung tumors using a markerless template-based tracking algorithm. Methods: Ten representative patient breathing patterns were programmed into a Quasar™ motion phantom. The phantom was modified by affixing pork ribs to the surface, and a cedar insert with a small spherical volume was used to simulate lung and tumor, respectively. Sequential 60 kVp (6 mA) and 120 kVp (1.5 mA) fluoroscopic sequences were acquired. Frame-by-frame weighted logarithmic subtraction was performed resulting in a DE fluoroscopic sequence. A template-based algorithm was then used to track tumor motion throughout the DE and SE fluoroscopy sequences. Tracking coordinates were evaluated against ground-truth tumor locations. Fluoroscopic images were also acquired for two lung cancer patients, neither of which had implanted fiducials. Results: For phantom imaging, a total of 1925 frames were analyzed. The algorithm successfully tracked the target on 99.9% (1923/1925) of DE frames vs 90.7% (1745/1925) SE images (p 5 mm displacements from the ground truth vs 0% for DE fluoroscopy. Conclusions: This work indicates the potential for markerless tumor tracking utilizing DE fluoroscopy. With DE imaging, the algorithm showed improved detectability vs SE fluoroscopy and was able to accurately track the tumor in nearly all cases.

Purpose: To evaluate the efficacy of dual energy (DE) vs. single energy (SE) fluoroscopic imaging in lung tumors using a markerless template-based tracking algorithm. Methods: Ten representative patient breathing patterns were programmed into a Quasar™ motion phantom. The phantom was modified by affixing pork ribs to the surface, and a cedar insert with a small spherical volume was used to simulate lung and tumor, respectively. Gated 60kVp(6mA) and 120kVp(1.5mA) fluoroscopic sequences were acquired using the Varian TrueBeam Integrated Imaging Solution. These high and low energy frames were subsequently aligned by phase and amplitude. Frame-by-frame weighted logarithmic subtraction was performed resulting in a DE fluoroscopic image sequence that highlighted soft tissue structures. A template-based algorithm was then used to track tumor motion throughout the sequence for DE and SE images (120kVp). Tracking coordinates were evaluated against ground truth tumor locations as identified by a physician. A displacement of greater than 3 mm was considered a non-successful track. The same process was also repeated for images obtained from 3 SBRT lung patients, none of which had implanted fiducials. Results: For phantom imaging, a total of 1925 frames were analyzed. The algorithm successfully tracked the target on 91.6%(1763/1925) of DE frames vs. 74.9%(1441/1923) SE images (p

Purpose: To compare markerless template-based tracking of lung tumors using dual energy (DE) cone-beam computed tomography (CBCT) projections versus single energy (SE) CBCT projections. Methods: A RANDO chest phantom with a simulated tumor in the upper right lung was used to investigate the effectiveness of tumor tracking using DE and SE CBCT projections. Planar kV projections from CBCT acquisitions were captured at 60 kVp (4 mAs) and 120 kVp (1 mAs) using the Varian TrueBeam and non-commercial iTools Capture software. Projections were taken at approximately every 0.53° while the gantry rotated. Due to limitations of the phantom, angles for which the shoulders blocked the tumor were excluded from tracking analysis. DE images were constructed using a weighted logarithmic subtraction that removed bony anatomy while preserving soft tissue structures. The tumors were tracked separately on DE and SE (120 kVp) images using a template-based tracking algorithm. The tracking results were compared to ground truth coordinates designated by a physician. Matches with a distance of greater than 3 mm from ground truth were designated as failing to track. Results: 363 frames were analyzed. The algorithm successfully tracked the tumor on 89.8% (326/363) of DE frames compared to 54.3% (197/363) of SE frames (p